摘要翻译：
从选择中发现偏好的能力是实证经济学和福利分析的基础。大量的证据表明选择是随机的，这导致了随机效用模型作为应用微观经济学的主导范式。然而，众所周知，在没有关于噪声结构的假设的情况下，不可能推断偏好的结构。这使得不可能独立于偏好的结构来实证检验噪声的结构。在这里，我们表明，如果扩大数据集以包括响应时间，就可以绕过这个困难。一个关于响应时间分布的简单条件（一阶随机优势的较弱版本）确保选择揭示偏好，而不假设效用噪声的结构。如果将分析局限于特定类型的模型，则会得到更清晰的结果。在对称噪声下，响应时间允许揭示数据集外的选择对的偏好，如果噪声是费希纳噪声，甚至可以预测样本外的选择概率。我们的结论是：经济学中的标准随机效用模型和心理学中的标准漂移-扩散模型必然产生满足我们关于响应时间分布的充分条件的数据集。
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英文标题：
《Time will tell - Recovering Preferences when Choices are Noisy》
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作者：
Carlos Alos-Ferrer, Ernst Fehr, Nick Netzer
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  The ability to uncover preferences from choices is fundamental for both positive economics and welfare analysis. Overwhelming evidence shows that choice is stochastic, which has given rise to random utility models as the dominant paradigm in applied microeconomics. However, as is well known, it is not possible to infer the structure of preferences in the absence of assumptions on the structure of noise. This makes it impossible to empirically test the structure of noise independently from the structure of preferences. Here, we show that the difficulty can be bypassed if data sets are enlarged to include response times. A simple condition on response time distributions (a weaker version of first order stochastic dominance) ensures that choices reveal preferences without assumptions on the structure of utility noise. Sharper results are obtained if the analysis is restricted to specific classes of models. Under symmetric noise, response times allow to uncover preferences for choice pairs outside the data set, and if noise is Fechnerian, even choice probabilities can be forecast out of sample. We conclude by showing that standard random utility models from economics and standard drift-diffusion models from psychology necessarily generate data sets fulfilling our sufficient condition on response time distributions.
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PDF链接：
https://arxiv.org/pdf/1811.02497